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BD #7 - 11 Attributes That Distinguish Senior Talent in Tech

How seniors take on more responsibility and deliver more reliably

Prompt: People climbing a ladder to a beautiful sky

Prompt: People climbing a ladder to a beautiful sky (made with Midjourney)

A common question amongst both data professionals and hiring managers:

What makes someone senior?

Spoiler alert: it isn't years of experience. While you often need several years to develop all of the necessary skills it isn't a hard requirement. Putting arbitrary thresholds onto these roles will lock out great talent and unfairly benefit mediocre people that have been around for a while.

Now, this can be tough to gauge, but I think there are a few critical attributes that more senior people display. First, there's definitely a technical component. You want someone that's been through the mill and developed the experience that only comes with making mistakes and finding the solutions.

Technical ability is a critical part of the puzzle, but getting more technical wouldn't make for great advice, so here we'll talk through the other components of a senior contributor.

First though, let's ask ourselves a better question...

What does it mean to be senior?

This is something many people don't have a good handle on.

Senior, Principal, Staff, and Head of positions all act as proxies for more better talent - people that should be able to do more. But that's not what it means.

My mentor once put it to me brilliantly:

"It's all about risk and uncertainty. The more senior you are, the more difficult, risky, and undefined the problem I should be able to hand you."

This has worked for me well over the years, and it's something I want you to consider.

Whereas both a data scientist and a senior data scientist might have the technical chops to deliver a great solution, I would expect a senior to better handle more complex situations. When the data is terrible, when the end-user isn't sure, when the use case isn't clear, when the team is struggling, a senior begins to stand out.

But first...

The attributes that matter most

What follows is an unordered list of behaviours and attributes that I believe are more common and better developed in more senior candidates.

If you're a data scientist looking to take the next step and get more responsibility, think about each of these and how they apply to your situation. Focus on one or two a month, get someone to help and give feedback and start improving each of these skills.

If you're a manager or leader looking to promote or hire people into senior positions, start thinking about these attributes. Don't just assess people's current ability but also their potential and trajectory - if someone is inexperienced but growing fast, that's a strong indicator of future potential.

In no particular order:

1. Get your solutions into production

Yes, some of you may be fortunate enough to work in an environment with mature MLOps processes. Or perhaps you're blessed with a friendly machine learning engineer to hold your hand. For the rest of us, it's common to be delivering data science with little support. Senior data scientists realise this and know that, without a route to production, their impact will be limited.

2. Listen to subject matter experts (SMEs) and stakeholders

You might know the most about machine learning and model stacking, but if you're applying that rare and expensive knowledge to the wrong problems in the wrong way, you're not going to deliver much value. Being able to deeply understand and listen to the people who will use your solutions will have a significant impact on your potential.

3. Build a reputation for value first

This might seem an odd one, but it's a mindset shift for some that I think is very important. Frame what you do and how you communicate your work around what value it will bring. Question your motives when taking some course of action - is this a value-driven decision? Once you start to embody this, others will notice, and that starts to build trust that you'll be acting in the company's best interest.

4. Pick up the less desirable tasks

This is something that aligns well with sound leadership principles - be the first person to take on the rubbish tasks. This gets you noticed as a team player and builds an environment where everyone wants to chip in.

5. Support others in their journey

The best way to learn is to teach. And you don't have to be an expert to teach someone something. Often, people one step ahead of you are the best person to show you the way because their perspective isn't too different - experts can sometimes struggle to relate to beginners. Teaching also indicates you're eager for the team to grow and it'll do wonders for your reputation across the organisation.

6. Network and seek mentorship

I've found mentors and my network to be invaluable in my growth. If you can't find them internally, reach out. Being able to ask questions and get feedback specific to your situation can help you shortcut many challenging issues. If you can't find anyone, ping me a message, and I'll see if I can connect you with someone.

7. Keep to your deadlines

This can sometimes fall outside your control but being known to deliver on time will, again, build trust and develop your reputation. If you're on a project that isn't going to hit the deadline, then be the person that reaches out to the stakeholders and works with them to find a compromise.

8. Lead some projects

Seems obvious again, but do whatever you can to lead a project or two. Tell leadership that you have ambitions to grow and that you want the opportunity. The worst they can say is no. If you're lucky, you'll get the chance to lead in a lower-risk setting and get feedback to help you develop.

9. Be a good follower

I think good leadership requires good followership. You need to know when to stand up and challenge but you also need to know when to get in line and play with the team (and not against it). This means accepting when things don't go your way and doing what you can to get on board (so long as it's not safety-critical or something absolutely unacceptable). If it indeed was a bad move you'll be safe having already voiced your concerns at the outset.

10. Communicate

Communication skills are vital to senior roles. You'll spend more and more time in meetings and aligning the work of others over just delivering alone. Learn how to express your ideas and collaborate through communication.

11. Listen

Finally - the most important. Listen. Listen well. Listen with intent.

None of the above matters if you're not taking on board the guidance and signals the universe is sending your way.

Final thoughts

Getting into data science is hard and progressing to more senior roles can be harder. There's no clear path, and it does take time. It's all about risk,

Show your colleagues you can reliably deliver great results, and the promotion will follow.

If you're looking for help, here are a few options:

  • For data professionals seeking help or wanting some 1-2-1 coaching, reach out to me on LinkedIn here or book a coaching session here

  • If you're an organisation looking for some assistance, email me at [email protected]

  • If you're interested in some packaged training or consulting services then... watch this space.

And finally, if you've enjoyed this or know someone who might find it useful, I'd greatly appreciate you sharing it with them 🙏

All the best.

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